Clustering
#FF7f00 - orange High methylation
#800080 - purple middling
#0000CD - blue low meth
# black - NA
#ensmbl
#ffff00 - yellow low meth
#19ff00 - green middle
#0033cc - blue high meth
col_fun <- colorRamp2(c(0, 0.5, 1), c("#ffff00", "#19ff00", "#0033cc"))
#col_fun <- colorRamp2(c(0, 0.5, 1), c("#0000CD", "#800080", "#FF7f00"))
# na_col = "black"
# col = col_fun
#tRNAprobes
tRNAProbeLookUp <-
tRNAmethCancerNormal %>%
dplyr::select(probeID,tRNAname) %>%
distinct()
tRNAProbeLookUpColour <- left_join(
tRNAProbeLookUp,
data.frame(
"colour"=colorspace::rainbow_hcl(tRNAProbeLookUp$tRNAname %>% unique() %>% length()),
"tRNAname"=tRNAProbeLookUp$tRNAname %>% unique()
),
by="tRNAname"
)
Column `tRNAname` joining character vector and factor, coercing into character vector
betasByTissue <-
tRNAmethCancerNormal %>%
#head(n=1000) %>%
dplyr::select(probeID,primary_site,Beta_value) %>%
group_by(primary_site) %>%
mutate(index = row_number()) %>%
spread(primary_site,Beta_value) %>%
dplyr::select(-index)
betasByTissueM <-
betasByTissue %>% dplyr::select(-probeID) %>% as.matrix()
rownames(betasByTissueM) <- betasByTissue$probeID
Cancer and Normal By Probe
betasByTissueX <-
tRNAmethCancerNormal %>%
#head(n=1000) %>%
dplyr::select(probeID,primary_site,Beta_value) %>%
group_by(primary_site) %>%
mutate(index = row_number()) %>%
spread(primary_site,Beta_value) %>%
dplyr::select(-index) #%>%
#as.matrix()
meanBetasByTissue <-
betasByTissueX %>%
group_by(probeID) %>%
summarise_all(mean,na.rm=TRUE)
meanBetasByTissueM <-
meanBetasByTissue %>%
dplyr::select(-probeID) %>%
as.matrix()
rownames(meanBetasByTissueM) <- meanBetasByTissue$probeID
meanBetasByTissueM <- meanBetasByTissueM %>% na.omit()
# tmp <- tRNAProbeLookUpColour %>%
# dplyr::filter(probeID %in% rownames(meanBetasByTissueM)) %>%
# pull(colour)
# names(tmp) <- tRNAProbeLookUpColour %>%
# dplyr::filter(probeID %in% rownames(meanBetasByTissueM)) %>%
# pull(tRNAname)
# tmp <- tmp %>% as.factor()
tmp <- tRNAProbeLookUpColour$colour
names(tmp) <- tRNAProbeLookUpColour$probeID
heatmaply::heatmaply(
meanBetasByTissueM#,
# row_side_colors = rownames(meanBetasByTissueM),
# row_side_palette = #tmp,
#RowSideColors = tmp
# tRNAProbeLookUpColour %>%
# dplyr::filter(probeID %in% rownames(meanBetasByTissueM)) %>%
# pull(colour)
)
'heatmap' objects don't have these attributes: 'showlegend'
Valid attributes include:
'type', 'visible', 'opacity', 'name', 'uid', 'ids', 'customdata', 'meta', 'hoverinfo', 'hoverlabel', 'stream', 'transforms', 'uirevision', 'z', 'x', 'x0', 'dx', 'y', 'y0', 'dy', 'text', 'hovertext', 'transpose', 'xtype', 'ytype', 'zsmooth', 'connectgaps', 'xgap', 'ygap', 'zhoverformat', 'hovertemplate', 'zauto', 'zmin', 'zmax', 'zmid', 'colorscale', 'autocolorscale', 'reversescale', 'showscale', 'colorbar', 'coloraxis', 'xcalendar', 'ycalendar', 'xaxis', 'yaxis', 'idssrc', 'customdatasrc', 'metasrc', 'hoverinfosrc', 'zsrc', 'xsrc', 'ysrc', 'textsrc', 'hovertextsrc', 'hovertemplatesrc', 'key', 'set', 'frame', 'transforms', '_isNestedKey', '_isSimpleKey', '_isGraticule', '_bbox'
'heatmap' objects don't have these attributes: 'showlegend'
Valid attributes include:
'type', 'visible', 'opacity', 'name', 'uid', 'ids', 'customdata', 'meta', 'hoverinfo', 'hoverlabel', 'stream', 'transforms', 'uirevision', 'z', 'x', 'x0', 'dx', 'y', 'y0', 'dy', 'text', 'hovertext', 'transpose', 'xtype', 'ytype', 'zsmooth', 'connectgaps', 'xgap', 'ygap', 'zhoverformat', 'hovertemplate', 'zauto', 'zmin', 'zmax', 'zmid', 'colorscale', 'autocolorscale', 'reversescale', 'showscale', 'colorbar', 'coloraxis', 'xcalendar', 'ycalendar', 'xaxis', 'yaxis', 'idssrc', 'customdatasrc', 'metasrc', 'hoverinfosrc', 'zsrc', 'xsrc', 'ysrc', 'textsrc', 'hovertextsrc', 'hovertemplatesrc', 'key', 'set', 'frame', 'transforms', '_isNestedKey', '_isSimpleKey', '_isGraticule', '_bbox'
#heatmaply::heatmapr(meanBetasByTissueM)
# meanBetasByTissueMna <-
# meanBetasByTissue %>%
# dplyr::select(-probeID) %>%
# as.matrix()
# rownames(meanBetasByTissueMna) <- meanBetasByTissue$probeID
#
# heatmaply_na(meanBetasByTissueMna) # !!!
Cancer and Normal by tRNA
betasByTissueT <-
tRNAmethCancerNormal %>%
#head(n=1000) %>%
dplyr::select(probeID,tRNAname,primary_site,Beta_value) %>%
group_by(primary_site) %>%
mutate(index = row_number()) %>%
spread(primary_site,Beta_value) %>%
dplyr::select(-index) #%>%
#as.matrix()
meanBetasByTissueT <-
betasByTissueT %>%
dplyr::select(-probeID) %>%
group_by(tRNAname) %>%
summarise_all(mean,na.rm=TRUE)
meanBetasByTissueTM <-
meanBetasByTissueT %>%
dplyr::select(-tRNAname) %>%
as.matrix()
rownames(meanBetasByTissueTM) <- meanBetasByTissueT$tRNAname
meanBetasByTissueTM <- meanBetasByTissueTM %>% na.omit()
heatmaply::heatmaply(
meanBetasByTissueTM,
main = "Mean methylation by tRNA across Cancer and Normal Samples",
limits=c(0,1)
)
'heatmap' objects don't have these attributes: 'showlegend'
Valid attributes include:
'type', 'visible', 'opacity', 'name', 'uid', 'ids', 'customdata', 'meta', 'hoverinfo', 'hoverlabel', 'stream', 'transforms', 'uirevision', 'z', 'x', 'x0', 'dx', 'y', 'y0', 'dy', 'text', 'hovertext', 'transpose', 'xtype', 'ytype', 'zsmooth', 'connectgaps', 'xgap', 'ygap', 'zhoverformat', 'hovertemplate', 'zauto', 'zmin', 'zmax', 'zmid', 'colorscale', 'autocolorscale', 'reversescale', 'showscale', 'colorbar', 'coloraxis', 'xcalendar', 'ycalendar', 'xaxis', 'yaxis', 'idssrc', 'customdatasrc', 'metasrc', 'hoverinfosrc', 'zsrc', 'xsrc', 'ysrc', 'textsrc', 'hovertextsrc', 'hovertemplatesrc', 'key', 'set', 'frame', 'transforms', '_isNestedKey', '_isSimpleKey', '_isGraticule', '_bbox'
'heatmap' objects don't have these attributes: 'showlegend'
Valid attributes include:
'type', 'visible', 'opacity', 'name', 'uid', 'ids', 'customdata', 'meta', 'hoverinfo', 'hoverlabel', 'stream', 'transforms', 'uirevision', 'z', 'x', 'x0', 'dx', 'y', 'y0', 'dy', 'text', 'hovertext', 'transpose', 'xtype', 'ytype', 'zsmooth', 'connectgaps', 'xgap', 'ygap', 'zhoverformat', 'hovertemplate', 'zauto', 'zmin', 'zmax', 'zmid', 'colorscale', 'autocolorscale', 'reversescale', 'showscale', 'colorbar', 'coloraxis', 'xcalendar', 'ycalendar', 'xaxis', 'yaxis', 'idssrc', 'customdatasrc', 'metasrc', 'hoverinfosrc', 'zsrc', 'xsrc', 'ysrc', 'textsrc', 'hovertextsrc', 'hovertemplatesrc', 'key', 'set', 'frame', 'transforms', '_isNestedKey', '_isSimpleKey', '_isGraticule', '_bbox'
#heatmaply::heatmapr(meanBetasByTissueM)
meanBetasByTissueTMHeatmap <-
meanBetasByTissueTM %>%
Heatmap(
heatmap_width = unit(5.5,"inches"),
heatmap_height = unit(7.5,"inches"),
column_title_gp = gpar(fontsize = 16, fontface = "bold"),
column_title = "Mean methylation by tRNA\nCombined Cancer and Normal Samples",
name = "Meth",
column_names_rot = 45,
column_names_gp = gpar(fontsize = 10),
row_names_gp = gpar(
fontsize = 10,
col = if_else(rownames(.) %in% tRNAgeBB,"red","black")
),
na_col = "black",
col = col_fun,
row_title = "tRNA gene"
)
png(
filename = "graphics/meanBetasByTissueTMHeatmap.png",
width = 7, height = 8, units = "in", res = 192
)
meanBetasByTissueTMHeatmap
dev.off()
jpeg
2
meanBetasByTissueTMHeatmap
meanBetasByTissueTMaaSplitHeatmap <-
meanBetasByTissueTM %>%
Heatmap(
#col = methColFunc,
heatmap_width = unit(5.5,"inches"),
heatmap_height = unit(7.5,"inches"),
column_title_gp = gpar(fontsize = 16, fontface = "bold"),
column_title = "Mean methylation by tRNA\nCombined Cancer and Normal Samples",
name = "Meth",
column_names_rot = 45,
column_names_gp = gpar(fontsize = 10),
row_split = rownames(.) %>%
gsub(pattern = "tRNA-(\\w+)-\\w+-\\w+-\\d+",replacement = "\\1"),
row_names_gp = gpar(
fontsize = 10,
col = if_else(rownames(.) %in% tRNAgeBB,"red","black")
),
na_col = "black",
col = col_fun,
row_title = "tRNA gene"
)
png(
filename = "graphics/meanBetasByTissueTMaaSplitHeatmap.png",
width = 7, height = 8, units = "in", res = 192
)
meanBetasByTissueTMaaSplitHeatmap
dev.off()
jpeg
2
meanBetasByTissueTMaaSplitHeatmap
Cancer by tRNA
betasByTissueTC <-
tRNAmethCancerNormal %>%
dplyr::filter(sample_type == "Primary Tumor") %>%
#head(n=1000) %>%
dplyr::select(probeID,tRNAname,primary_site,Beta_value) %>%
group_by(primary_site) %>%
mutate(index = row_number()) %>%
spread(primary_site,Beta_value) %>%
dplyr::select(-index) #%>%
#as.matrix()
meanBetasByTissueTC <-
betasByTissueTC %>%
dplyr::select(-probeID) %>%
group_by(tRNAname) %>%
summarise_all(mean,na.rm=TRUE)
meanBetasByTissueTCM <-
meanBetasByTissueTC %>%
dplyr::select(-tRNAname) %>%
as.matrix()
rownames(meanBetasByTissueTCM) <- meanBetasByTissueTC$tRNAname
meanBetasByTissueTCM <- meanBetasByTissueTCM %>% na.omit()
heatmaply::heatmaply(
meanBetasByTissueTCM,
main = "Mean methylation by tRNA In Primary Tumour Samples",
limits=c(0,1)
)
'heatmap' objects don't have these attributes: 'showlegend'
Valid attributes include:
'type', 'visible', 'opacity', 'name', 'uid', 'ids', 'customdata', 'meta', 'hoverinfo', 'hoverlabel', 'stream', 'transforms', 'uirevision', 'z', 'x', 'x0', 'dx', 'y', 'y0', 'dy', 'text', 'hovertext', 'transpose', 'xtype', 'ytype', 'zsmooth', 'connectgaps', 'xgap', 'ygap', 'zhoverformat', 'hovertemplate', 'zauto', 'zmin', 'zmax', 'zmid', 'colorscale', 'autocolorscale', 'reversescale', 'showscale', 'colorbar', 'coloraxis', 'xcalendar', 'ycalendar', 'xaxis', 'yaxis', 'idssrc', 'customdatasrc', 'metasrc', 'hoverinfosrc', 'zsrc', 'xsrc', 'ysrc', 'textsrc', 'hovertextsrc', 'hovertemplatesrc', 'key', 'set', 'frame', 'transforms', '_isNestedKey', '_isSimpleKey', '_isGraticule', '_bbox'
'heatmap' objects don't have these attributes: 'showlegend'
Valid attributes include:
'type', 'visible', 'opacity', 'name', 'uid', 'ids', 'customdata', 'meta', 'hoverinfo', 'hoverlabel', 'stream', 'transforms', 'uirevision', 'z', 'x', 'x0', 'dx', 'y', 'y0', 'dy', 'text', 'hovertext', 'transpose', 'xtype', 'ytype', 'zsmooth', 'connectgaps', 'xgap', 'ygap', 'zhoverformat', 'hovertemplate', 'zauto', 'zmin', 'zmax', 'zmid', 'colorscale', 'autocolorscale', 'reversescale', 'showscale', 'colorbar', 'coloraxis', 'xcalendar', 'ycalendar', 'xaxis', 'yaxis', 'idssrc', 'customdatasrc', 'metasrc', 'hoverinfosrc', 'zsrc', 'xsrc', 'ysrc', 'textsrc', 'hovertextsrc', 'hovertemplatesrc', 'key', 'set', 'frame', 'transforms', '_isNestedKey', '_isSimpleKey', '_isGraticule', '_bbox'
#heatmaply::heatmapr(meanBetasByTissueM)
meanBetasByTissueTCMHeatmap <-
meanBetasByTissueTCM %>%
Heatmap(
heatmap_width = unit(5.5,"inches"),
heatmap_height = unit(7.5,"inches"),
column_title_gp = gpar(fontsize = 16, fontface = "bold"),
column_title = "Mean methylation by tRNA\nIn Primary Tumour Samples",
name = "Meth",
column_names_rot = 45,
column_names_gp = gpar(fontsize = 10),
row_names_gp = gpar(
fontsize = 10,
col = if_else(rownames(.) %in% tRNAgeBB,"red","black")
),
na_col = "black",
col = col_fun,
row_title = "tRNA gene"
)
png(
filename = "graphics/meanBetasByTissueTCMHeatmap.png",
width = 7, height = 8, units = "in", res = 192
)
meanBetasByTissueTCMHeatmap
dev.off()
jpeg
2
meanBetasByTissueTCMHeatmap
meanBetasByTissueTCMaaSplitHeatmap <-
meanBetasByTissueTCM %>%
Heatmap(
#col = methColFunc,
heatmap_width = unit(5.5,"inches"),
heatmap_height = unit(7.5,"inches"),
column_title_gp = gpar(fontsize = 16, fontface = "bold"),
column_title = "Mean methylation by tRNA\nIn Primary Tumour Samples",
name = "Meth",
column_names_rot = 45,
column_names_gp = gpar(fontsize = 10),
row_split = rownames(.) %>%
gsub(pattern = "tRNA-(\\w+)-\\w+-\\w+-\\d+",replacement = "\\1"),
row_names_gp = gpar(
fontsize = 10,
col = if_else(rownames(.) %in% tRNAgeBB,"red","black")
),
na_col = "black",
col = col_fun,
row_title = "tRNA gene"
)
png(
filename = "graphics/meanBetasByTissueTCMaaSplitHeatmap.png",
width = 7, height = 8, units = "in", res = 192
)
meanBetasByTissueTCMaaSplitHeatmap
dev.off()
jpeg
2
meanBetasByTissueTCMaaSplitHeatmap
Normal by tRNA
betasByTissueTN <-
tRNAmethCancerNormal %>%
dplyr::filter(sample_type == "Solid Tissue Normal") %>%
#head(n=1000) %>%
dplyr::select(probeID,tRNAname,primary_site,Beta_value) %>%
group_by(primary_site) %>%
mutate(index = row_number()) %>%
spread(primary_site,Beta_value) %>%
dplyr::select(-index) #%>%
#as.matrix()
meanBetasByTissueTN <-
betasByTissueTN %>%
dplyr::select(-probeID) %>%
group_by(tRNAname) %>%
summarise_all(mean,na.rm=TRUE)
meanBetasByTissueTNM <-
meanBetasByTissueTN %>%
dplyr::select(-tRNAname) %>%
as.matrix()
rownames(meanBetasByTissueTNM) <- meanBetasByTissueTN$tRNAname
meanBetasByTissueTNM <- meanBetasByTissueTNM %>% na.omit()
heatmaply::heatmaply(
meanBetasByTissueTNM,
main = "Mean methylation by tRNA In Solid Tissue Normal Samples",
limits=c(0,1)
)
'heatmap' objects don't have these attributes: 'showlegend'
Valid attributes include:
'type', 'visible', 'opacity', 'name', 'uid', 'ids', 'customdata', 'meta', 'hoverinfo', 'hoverlabel', 'stream', 'transforms', 'uirevision', 'z', 'x', 'x0', 'dx', 'y', 'y0', 'dy', 'text', 'hovertext', 'transpose', 'xtype', 'ytype', 'zsmooth', 'connectgaps', 'xgap', 'ygap', 'zhoverformat', 'hovertemplate', 'zauto', 'zmin', 'zmax', 'zmid', 'colorscale', 'autocolorscale', 'reversescale', 'showscale', 'colorbar', 'coloraxis', 'xcalendar', 'ycalendar', 'xaxis', 'yaxis', 'idssrc', 'customdatasrc', 'metasrc', 'hoverinfosrc', 'zsrc', 'xsrc', 'ysrc', 'textsrc', 'hovertextsrc', 'hovertemplatesrc', 'key', 'set', 'frame', 'transforms', '_isNestedKey', '_isSimpleKey', '_isGraticule', '_bbox'
'heatmap' objects don't have these attributes: 'showlegend'
Valid attributes include:
'type', 'visible', 'opacity', 'name', 'uid', 'ids', 'customdata', 'meta', 'hoverinfo', 'hoverlabel', 'stream', 'transforms', 'uirevision', 'z', 'x', 'x0', 'dx', 'y', 'y0', 'dy', 'text', 'hovertext', 'transpose', 'xtype', 'ytype', 'zsmooth', 'connectgaps', 'xgap', 'ygap', 'zhoverformat', 'hovertemplate', 'zauto', 'zmin', 'zmax', 'zmid', 'colorscale', 'autocolorscale', 'reversescale', 'showscale', 'colorbar', 'coloraxis', 'xcalendar', 'ycalendar', 'xaxis', 'yaxis', 'idssrc', 'customdatasrc', 'metasrc', 'hoverinfosrc', 'zsrc', 'xsrc', 'ysrc', 'textsrc', 'hovertextsrc', 'hovertemplatesrc', 'key', 'set', 'frame', 'transforms', '_isNestedKey', '_isSimpleKey', '_isGraticule', '_bbox'
#heatmaply::heatmapr(meanBetasByTissueM)
#tRNAgeBB
#methColFunc <- circlize::colorRamp2(c(0,0.5,1),c("blue","white","orange"))
meanBetasByTissueTNMHeatmap <-
meanBetasByTissueTNM %>%
Heatmap(
heatmap_width = unit(5.5,"inches"),
heatmap_height = unit(7.5,"inches"),
column_title_gp = gpar(fontsize = 16, fontface = "bold"),
column_title = "Mean methylation by tRNA\nIn Solid Tissue Normal Samples",
name = "Meth",
column_names_rot = 45,
column_names_gp = gpar(fontsize = 10),
row_names_gp = gpar(
fontsize = 10,
col = if_else(rownames(.) %in% tRNAgeBB,"red","black")
),
na_col = "black",
col = col_fun,
row_title = "tRNA gene"
)
png(
filename = "graphics/meanBetasByTissueTNMHeatmap.png",
width = 7, height = 8, units = "in", res = 192
)
meanBetasByTissueTNMHeatmap
dev.off()
null device
1
meanBetasByTissueTNMHeatmap

meanBetasByTissueTNMaaSplitHeatmap <-
meanBetasByTissueTNM %>%
Heatmap(
#col = methColFunc,
heatmap_width = unit(5.5,"inches"),
heatmap_height = unit(7.5,"inches"),
column_title_gp = gpar(fontsize = 16, fontface = "bold"),
column_title = "Mean methylation by tRNA\nIn Solid Tissue Normal Samples",
name = "Meth",
column_names_rot = 45,
column_names_gp = gpar(fontsize = 10),
row_split = rownames(.) %>%
gsub(pattern = "tRNA-(\\w+)-\\w+-\\w+-\\d+",replacement = "\\1"),
row_names_gp = gpar(
fontsize = 10,
col = if_else(rownames(.) %in% tRNAgeBB,"red","black")
),
na_col = "black",
col = col_fun,
row_title = "tRNA gene"
)
png(
filename = "graphics/meanBetasByTissueTNMaaSplitHeatmap.png",
width = 7, height = 8, units = "in", res = 192
)
meanBetasByTissueTNMaaSplitHeatmap
dev.off()
null device
1
meanBetasByTissueTNMaaSplitHeatmap

pseudoSplit <- tRNA$pseudo
names(pseudoSplit) <- tRNA$tRNAname
meanBetasByTissueTNMpseudoSplitHeatmap <-
meanBetasByTissueTNM %>%
Heatmap(
#col = methColFunc,
heatmap_width = unit(5.5,"inches"),
heatmap_height = unit(7.5,"inches"),
column_title_gp = gpar(fontsize = 16, fontface = "bold"),
column_title = "Mean methylation by tRNA\nIn Solid Tissue Normal Samples",
name = "Meth",
column_names_rot = 45,
column_names_gp = gpar(fontsize = 10),
row_split = pseudoSplit[rownames(.)],
row_names_gp = gpar(
fontsize = 10,
col = if_else(rownames(.) %in% tRNAgeBB,"red","black")
),
na_col = "black",
col = col_fun,
row_title = "tRNA gene"
)
png(
filename = "graphics/meanBetasByTissueTNMpseudoSplitHeatmap.png",
width = 7, height = 8, units = "in", res = 192
)
meanBetasByTissueTNMpseudoSplitHeatmap
dev.off()
null device
1
meanBetasByTissueTNMpseudoSplitHeatmap

meanBetasByTissueTNM %>% dim()
[1] 43 19
#meanBetasByTissueTNM %>% rownames()
meanBetasByTissueTCM %>% dim()
[1] 42 19
#meanBetasByTissueTCM %>% rownames()
meanBetasByTissueTCMx <- meanBetasByTissueTNM[meanBetasByTissueTCM %>% rownames(),]
heatmaply::heatmaply(
file = "graphics/changeDNANormCancerbytRNA.html",
(meanBetasByTissueTCM - meanBetasByTissueTCMx),
#(meanBetasByTissueTCM - meanBetasByTissueTCMx)/meanBetasByTissueTCMx,
main = "Differnce between Mean methylation in Normal and Cancer Samples by tRNA (Cancer - Normal)",
limits=c(-1,1)
)
'heatmap' objects don't have these attributes: 'showlegend'
Valid attributes include:
'type', 'visible', 'opacity', 'name', 'uid', 'ids', 'customdata', 'meta', 'hoverinfo', 'hoverlabel', 'stream', 'transforms', 'uirevision', 'z', 'x', 'x0', 'dx', 'y', 'y0', 'dy', 'text', 'hovertext', 'transpose', 'xtype', 'ytype', 'zsmooth', 'connectgaps', 'xgap', 'ygap', 'zhoverformat', 'hovertemplate', 'zauto', 'zmin', 'zmax', 'zmid', 'colorscale', 'autocolorscale', 'reversescale', 'showscale', 'colorbar', 'coloraxis', 'xcalendar', 'ycalendar', 'xaxis', 'yaxis', 'idssrc', 'customdatasrc', 'metasrc', 'hoverinfosrc', 'zsrc', 'xsrc', 'ysrc', 'textsrc', 'hovertextsrc', 'hovertemplatesrc', 'key', 'set', 'frame', 'transforms', '_isNestedKey', '_isSimpleKey', '_isGraticule', '_bbox'
'heatmap' objects don't have these attributes: 'showlegend'
Valid attributes include:
'type', 'visible', 'opacity', 'name', 'uid', 'ids', 'customdata', 'meta', 'hoverinfo', 'hoverlabel', 'stream', 'transforms', 'uirevision', 'z', 'x', 'x0', 'dx', 'y', 'y0', 'dy', 'text', 'hovertext', 'transpose', 'xtype', 'ytype', 'zsmooth', 'connectgaps', 'xgap', 'ygap', 'zhoverformat', 'hovertemplate', 'zauto', 'zmin', 'zmax', 'zmid', 'colorscale', 'autocolorscale', 'reversescale', 'showscale', 'colorbar', 'coloraxis', 'xcalendar', 'ycalendar', 'xaxis', 'yaxis', 'idssrc', 'customdatasrc', 'metasrc', 'hoverinfosrc', 'zsrc', 'xsrc', 'ysrc', 'textsrc', 'hovertextsrc', 'hovertemplatesrc', 'key', 'set', 'frame', 'transforms', '_isNestedKey', '_isSimpleKey', '_isGraticule', '_bbox'
'heatmap' objects don't have these attributes: 'showlegend'
Valid attributes include:
'type', 'visible', 'opacity', 'name', 'uid', 'ids', 'customdata', 'meta', 'hoverinfo', 'hoverlabel', 'stream', 'transforms', 'uirevision', 'z', 'x', 'x0', 'dx', 'y', 'y0', 'dy', 'text', 'hovertext', 'transpose', 'xtype', 'ytype', 'zsmooth', 'connectgaps', 'xgap', 'ygap', 'zhoverformat', 'hovertemplate', 'zauto', 'zmin', 'zmax', 'zmid', 'colorscale', 'autocolorscale', 'reversescale', 'showscale', 'colorbar', 'coloraxis', 'xcalendar', 'ycalendar', 'xaxis', 'yaxis', 'idssrc', 'customdatasrc', 'metasrc', 'hoverinfosrc', 'zsrc', 'xsrc', 'ysrc', 'textsrc', 'hovertextsrc', 'hovertemplatesrc', 'key', 'set', 'frame', 'transforms', '_isNestedKey', '_isSimpleKey', '_isGraticule', '_bbox'
---
title: "03 - GenomicDataCommons Normal Vs. Cancer tissue tRNA gene methylation - Clustering"
author: "Richard J. Acton"
date: "`r Sys.Date()`"
output:
  html_document:
    df_print: paged
    fig_caption: yes
    number_sections: yes
    toc: yes
    toc_float: yes
  html_notebook:
    fig_caption: yes
    number_sections: yes
    toc: yes
    toc_float: yes
bibliography: "`r normalizePath('../library.bib')`"
---

# Set-up

## Environment

```{r}
if(!dir.exists("graphics")) {
	dir.create("graphics", showWarnings = FALSE, recursive = TRUE)
}
```

## libs

```{r}
suppressPackageStartupMessages({
	library(tidyverse)
	library(lubridate)
	library(broom)
	library(psych)
	library(heatmaply)
	library(patchwork)
	library(ComplexHeatmap)
	library(circlize)
})
```

## Data Read-In

### tRNA array probes

```{r}
tRNAprobes <- 
read_delim(	
	delim = "\t",
	file = "../tRNA-GtRNAdb/450k_coresponding_hg19tRNAs.bed",
	col_types = "ciicciiciciicccc",
	col_names = c("pChr","pStart","pEnd","probeID",
		as.character(
			read_delim(
				delim = "\t",
				file = "../tRNA-GtRNAdb/std_tRNA_header.txt",
				col_names = FALSE,
				col_types = paste0(rep("c",12),collapse = "")
			)
		)
	)
)

```

### tRNAge gene set

```{r}
tRNAge <- read_delim(
	delim = "\t",
	 col_names = "tRNAname",
	 col_types = "c",
	 file = "../tRNA-GtRNAdb/GenWideSigWintRNAs.txt"
) %>%
	pull()

tRNAgeBB <- read_delim(
	delim = "\t",
	 col_names = "tRNAname",
	 col_types = "c",
	 file = "../tRNA-GtRNAdb/BB_GWS_tRNA.txt"
) %>%
	pull()
```

### tRNA gene data

```{r}
tRNA <- read.table("../tRNA-GtRNAdb/hg19-tRNAs-SeqStrPseu.bed") 

colnames(tRNA) <- 
c(
	as.character(
		read.table(
			"../tRNA-GtRNAdb/std_tRNA_header.txt",
			stringsAsFactors = FALSE
		)
	),
	"pseudo","str","seq"
)

tRNA <- tRNA %>%
	extract(tRNAname,
			c("nmt","aa","codon"),
			"(\\w*)-?tRNA-(i?\\w{3})(?:\\w+)?-(\\w+)-",
			remove = FALSE
	)

```

### Methylation Data

```{r}
dataTest <- readRDS(
	file = "data/tRNAprobesNormCancerArrayPairs.Rds"
)
```

```{r}
dataTest %>%  dplyr::as_tibble() %>% distinct(case_id,age) %>% nrow()
range(dataTest$age)
```

```{r}
tRNAmethCancerNormal <- dataTest %>% 
	unnest() %>% 
	as_tibble() %>%
	filter(sample_type %in% c("Solid Tissue Normal", "Primary Tumor")) %>%
	mutate(tRNAge = tRNAname %in% tRNAge) %>%
	filter(!is.na(Beta_value))

```

# Clustering

```{r}
#FF7f00 - orange High methylation
#800080 - purple middling
#0000CD - blue low meth
# black - NA

#ensmbl
#ffff00 - yellow low meth
#19ff00 - green middle
#0033cc - blue high meth

col_fun <- colorRamp2(c(0, 0.5, 1), c("#ffff00", "#19ff00", "#0033cc"))
#col_fun <- colorRamp2(c(0, 0.5, 1), c("#0000CD", "#800080", "#FF7f00"))
# na_col = "black"
# col = col_fun

```

```{r}
#tRNAprobes
tRNAProbeLookUp <- 
tRNAmethCancerNormal %>% 
	dplyr::select(probeID,tRNAname) %>% 
	distinct()

tRNAProbeLookUpColour <- left_join(
	tRNAProbeLookUp,
	data.frame(
		"colour"=colorspace::rainbow_hcl(tRNAProbeLookUp$tRNAname %>% unique() %>% length()),
		"tRNAname"=tRNAProbeLookUp$tRNAname %>% unique()
	),
	by="tRNAname"
)
```

```{r}
betasByTissue <- 
tRNAmethCancerNormal %>% 
	#head(n=1000) %>% 
	dplyr::select(probeID,primary_site,Beta_value) %>% 
	group_by(primary_site) %>%
	mutate(index = row_number()) %>%
	spread(primary_site,Beta_value) %>%
	dplyr::select(-index)

betasByTissueM <- 
betasByTissue %>% dplyr::select(-probeID) %>% as.matrix()
rownames(betasByTissueM) <- betasByTissue$probeID

```

## Cancer and Normal By Probe

```{r, fig.height = 8, fig.width = 7}
betasByTissueX <- 
tRNAmethCancerNormal %>% 
	#head(n=1000) %>% 
	dplyr::select(probeID,primary_site,Beta_value) %>% 
	group_by(primary_site) %>%
	mutate(index = row_number()) %>%
	spread(primary_site,Beta_value) %>%
	dplyr::select(-index) #%>%
	#as.matrix() 
meanBetasByTissue <- 
betasByTissueX %>% 
	group_by(probeID) %>%
	summarise_all(mean,na.rm=TRUE)


meanBetasByTissueM <- 
meanBetasByTissue %>% 
	dplyr::select(-probeID) %>% 
	as.matrix()
rownames(meanBetasByTissueM) <- meanBetasByTissue$probeID
meanBetasByTissueM <- meanBetasByTissueM %>% na.omit()

# tmp <- tRNAProbeLookUpColour %>% 
# 		dplyr::filter(probeID %in% rownames(meanBetasByTissueM)) %>% 
# 		pull(colour)
# names(tmp) <- tRNAProbeLookUpColour %>% 
# 		dplyr::filter(probeID %in% rownames(meanBetasByTissueM)) %>% 
# 		pull(tRNAname)
# tmp <- tmp %>% as.factor()

tmp <- tRNAProbeLookUpColour$colour
names(tmp) <- tRNAProbeLookUpColour$probeID 

heatmaply::heatmaply(
	meanBetasByTissueM#,
	# row_side_colors = rownames(meanBetasByTissueM),
	# row_side_palette = #tmp,
	
	#RowSideColors = tmp
		# tRNAProbeLookUpColour %>% 
		# dplyr::filter(probeID %in% rownames(meanBetasByTissueM)) %>% 
		# pull(colour)
)
#heatmaply::heatmapr(meanBetasByTissueM)
```

```{r}
# meanBetasByTissueMna <- 
# meanBetasByTissue %>% 
# 	dplyr::select(-probeID) %>% 
# 	as.matrix()
# rownames(meanBetasByTissueMna) <- meanBetasByTissue$probeID
# 
# heatmaply_na(meanBetasByTissueMna) # !!!
```

## Cancer and Normal by tRNA

```{r, fig.height = 8, fig.width = 7}
betasByTissueT <- 
tRNAmethCancerNormal %>% 
	#head(n=1000) %>% 
	dplyr::select(probeID,tRNAname,primary_site,Beta_value) %>% 
	group_by(primary_site) %>%
	mutate(index = row_number()) %>%
	spread(primary_site,Beta_value) %>%
	dplyr::select(-index) #%>%
	#as.matrix() 
meanBetasByTissueT <- 
betasByTissueT %>% 
	dplyr::select(-probeID) %>%
	group_by(tRNAname) %>%
	summarise_all(mean,na.rm=TRUE)


meanBetasByTissueTM <- 
meanBetasByTissueT %>% 
	dplyr::select(-tRNAname) %>% 
	as.matrix()
rownames(meanBetasByTissueTM) <- meanBetasByTissueT$tRNAname
meanBetasByTissueTM <- meanBetasByTissueTM %>% na.omit()

heatmaply::heatmaply(
	meanBetasByTissueTM,
	main = "Mean methylation by tRNA across Cancer and Normal Samples",
	limits=c(0,1)
)
#heatmaply::heatmapr(meanBetasByTissueM)

meanBetasByTissueTMHeatmap <- 
meanBetasByTissueTM %>%
Heatmap(
	heatmap_width = unit(5.5,"inches"),
	heatmap_height = unit(7.5,"inches"),
	column_title_gp = gpar(fontsize = 16, fontface = "bold"),
	column_title = "Mean methylation by tRNA\nCombined Cancer and Normal Samples",
	name = "Meth",
	column_names_rot = 45,
	column_names_gp = gpar(fontsize = 10),
	row_names_gp = gpar(
		fontsize = 10,
		col = if_else(rownames(.) %in% tRNAgeBB,"red","black")
	),
	na_col = "black",
	col = col_fun,
	row_title = "tRNA gene"
)


png(
	filename = "graphics/meanBetasByTissueTMHeatmap.png",
	width = 7, height = 8, units = "in", res = 192
)
meanBetasByTissueTMHeatmap
dev.off()

meanBetasByTissueTMHeatmap

meanBetasByTissueTMaaSplitHeatmap <- 
meanBetasByTissueTM %>%
Heatmap(
	#col = methColFunc,
	heatmap_width = unit(5.5,"inches"),
	heatmap_height = unit(7.5,"inches"),
	column_title_gp = gpar(fontsize = 16, fontface = "bold"),
	column_title = "Mean methylation by tRNA\nCombined Cancer and Normal Samples",
	name = "Meth",
	column_names_rot = 45,
	column_names_gp = gpar(fontsize = 10),
	row_split = rownames(.) %>%
		gsub(pattern = "tRNA-(\\w+)-\\w+-\\w+-\\d+",replacement = "\\1"),
	row_names_gp = gpar(
		fontsize = 10,
		col = if_else(rownames(.) %in% tRNAgeBB,"red","black")
	),
	na_col = "black",
	col = col_fun,
	row_title = "tRNA gene"
)

png(
	filename = "graphics/meanBetasByTissueTMaaSplitHeatmap.png",
	width = 7, height = 8, units = "in", res = 192
)
meanBetasByTissueTMaaSplitHeatmap
dev.off()

meanBetasByTissueTMaaSplitHeatmap
```

## Cancer by tRNA

```{r,fig.height=8,fig.width=7}
betasByTissueTC <- 
tRNAmethCancerNormal %>% 
	dplyr::filter(sample_type == "Primary Tumor") %>%
	#head(n=1000) %>% 
	dplyr::select(probeID,tRNAname,primary_site,Beta_value) %>% 
	group_by(primary_site) %>%
	mutate(index = row_number()) %>%
	spread(primary_site,Beta_value) %>%
	dplyr::select(-index) #%>%
	#as.matrix() 
meanBetasByTissueTC <- 
betasByTissueTC %>% 
	dplyr::select(-probeID) %>%
	group_by(tRNAname) %>%
	summarise_all(mean,na.rm=TRUE)


meanBetasByTissueTCM <- 
meanBetasByTissueTC %>% 
	dplyr::select(-tRNAname) %>% 
	as.matrix()
rownames(meanBetasByTissueTCM) <- meanBetasByTissueTC$tRNAname
meanBetasByTissueTCM <- meanBetasByTissueTCM %>% na.omit()

heatmaply::heatmaply(
	meanBetasByTissueTCM,
	main = "Mean methylation by tRNA In Primary Tumour Samples",
	limits=c(0,1)
)
#heatmaply::heatmapr(meanBetasByTissueM)

meanBetasByTissueTCMHeatmap <- 
meanBetasByTissueTCM %>%
Heatmap(
	heatmap_width = unit(5.5,"inches"),
	heatmap_height = unit(7.5,"inches"),
	column_title_gp = gpar(fontsize = 16, fontface = "bold"),
	column_title = "Mean methylation by tRNA\nIn Primary Tumour Samples",
	name = "Meth",
	column_names_rot = 45,
	column_names_gp = gpar(fontsize = 10),
	row_names_gp = gpar(
		fontsize = 10,
		col = if_else(rownames(.) %in% tRNAgeBB,"red","black")
	),
	na_col = "black",
	col = col_fun,
	row_title = "tRNA gene"
)


png(
	filename = "graphics/meanBetasByTissueTCMHeatmap.png",
	width = 7, height = 8, units = "in", res = 192
)
meanBetasByTissueTCMHeatmap
dev.off()

meanBetasByTissueTCMHeatmap

meanBetasByTissueTCMaaSplitHeatmap <- 
meanBetasByTissueTCM %>%
Heatmap(
	#col = methColFunc,
	heatmap_width = unit(5.5,"inches"),
	heatmap_height = unit(7.5,"inches"),
	column_title_gp = gpar(fontsize = 16, fontface = "bold"),
	column_title = "Mean methylation by tRNA\nIn Primary Tumour Samples",
	name = "Meth",
	column_names_rot = 45,
	column_names_gp = gpar(fontsize = 10),
	row_split = rownames(.) %>%
		gsub(pattern = "tRNA-(\\w+)-\\w+-\\w+-\\d+",replacement = "\\1"),
	row_names_gp = gpar(
		fontsize = 10,
		col = if_else(rownames(.) %in% tRNAgeBB,"red","black")
	),
	na_col = "black",
	col = col_fun,
	row_title = "tRNA gene"
)

png(
	filename = "graphics/meanBetasByTissueTCMaaSplitHeatmap.png",
	width = 7, height = 8, units = "in", res = 192
)
meanBetasByTissueTCMaaSplitHeatmap
dev.off()

meanBetasByTissueTCMaaSplitHeatmap
```

## Normal by tRNA

```{r,fig.height=8,fig.width=7}
betasByTissueTN <- 
tRNAmethCancerNormal %>% 
	dplyr::filter(sample_type == "Solid Tissue Normal") %>%
	#head(n=1000) %>% 
	dplyr::select(probeID,tRNAname,primary_site,Beta_value) %>% 
	group_by(primary_site) %>%
	mutate(index = row_number()) %>%
	spread(primary_site,Beta_value) %>%
	dplyr::select(-index) #%>%
	#as.matrix() 
meanBetasByTissueTN <- 
betasByTissueTN %>% 
	dplyr::select(-probeID) %>%
	group_by(tRNAname) %>%
	summarise_all(mean,na.rm=TRUE)


meanBetasByTissueTNM <- 
meanBetasByTissueTN %>% 
	dplyr::select(-tRNAname) %>% 
	as.matrix()
rownames(meanBetasByTissueTNM) <- meanBetasByTissueTN$tRNAname
meanBetasByTissueTNM <- meanBetasByTissueTNM %>% na.omit()

heatmaply::heatmaply(
	meanBetasByTissueTNM,
	main = "Mean methylation by tRNA In Solid Tissue Normal Samples",
	limits=c(0,1)
)
#heatmaply::heatmapr(meanBetasByTissueM)
#tRNAgeBB
```

```{r}
#methColFunc <- circlize::colorRamp2(c(0,0.5,1),c("blue","white","orange"))
meanBetasByTissueTNMHeatmap <- 
meanBetasByTissueTNM %>%
Heatmap(
	heatmap_width = unit(5.5,"inches"),
	heatmap_height = unit(7.5,"inches"),
	column_title_gp = gpar(fontsize = 16, fontface = "bold"),
	column_title = "Mean methylation by tRNA\nIn Solid Tissue Normal Samples",
	name = "Meth",
	column_names_rot = 45,
	column_names_gp = gpar(fontsize = 10),
	row_names_gp = gpar(
		fontsize = 10,
		col = if_else(rownames(.) %in% tRNAgeBB,"red","black")
	),
	na_col = "black",
	col = col_fun,
	row_title = "tRNA gene"
)

png(
	filename = "graphics/meanBetasByTissueTNMHeatmap.png",
	width = 7, height = 8, units = "in", res = 192
)
meanBetasByTissueTNMHeatmap
dev.off()

meanBetasByTissueTNMHeatmap
```

```{r}
meanBetasByTissueTNMaaSplitHeatmap <- 
meanBetasByTissueTNM %>%
Heatmap(
	#col = methColFunc,
	heatmap_width = unit(5.5,"inches"),
	heatmap_height = unit(7.5,"inches"),
	column_title_gp = gpar(fontsize = 16, fontface = "bold"),
	column_title = "Mean methylation by tRNA\nIn Solid Tissue Normal Samples",
	name = "Meth",
	column_names_rot = 45,
	column_names_gp = gpar(fontsize = 10),
	row_split = rownames(.) %>%
		gsub(pattern = "tRNA-(\\w+)-\\w+-\\w+-\\d+",replacement = "\\1"),
	row_names_gp = gpar(
		fontsize = 10,
		col = if_else(rownames(.) %in% tRNAgeBB,"red","black")
	),
	na_col = "black",
	col = col_fun,
	row_title = "tRNA gene"
)

png(
	filename = "graphics/meanBetasByTissueTNMaaSplitHeatmap.png",
	width = 7, height = 8, units = "in", res = 192
)
meanBetasByTissueTNMaaSplitHeatmap
dev.off()

meanBetasByTissueTNMaaSplitHeatmap
```

```{r,fig.width=7,fig.height=7}
pseudoSplit <- tRNA$pseudo
names(pseudoSplit) <- tRNA$tRNAname

meanBetasByTissueTNMpseudoSplitHeatmap <- 
meanBetasByTissueTNM %>%
Heatmap(
	#col = methColFunc,
	heatmap_width = unit(5.5,"inches"),
	heatmap_height = unit(7.5,"inches"),
	column_title_gp = gpar(fontsize = 16, fontface = "bold"),
	column_title = "Mean methylation by tRNA\nIn Solid Tissue Normal Samples",
	name = "Meth",
	column_names_rot = 45,
	column_names_gp = gpar(fontsize = 10),
	row_split = pseudoSplit[rownames(.)],
	row_names_gp = gpar(
		fontsize = 10,
		col = if_else(rownames(.) %in% tRNAgeBB,"red","black")
	),
	na_col = "black",
	col = col_fun,
	row_title = "tRNA gene"
)

png(
	filename = "graphics/meanBetasByTissueTNMpseudoSplitHeatmap.png",
	width = 7, height = 8, units = "in", res = 192
)
meanBetasByTissueTNMpseudoSplitHeatmap
dev.off()

meanBetasByTissueTNMpseudoSplitHeatmap
```

```{r}
meanBetasByTissueTNM %>% dim()
#meanBetasByTissueTNM %>% rownames()

meanBetasByTissueTCM %>% dim()
#meanBetasByTissueTCM %>% rownames()
```

```{r,fig.height=8,fig.width=7}
meanBetasByTissueTCMx <- meanBetasByTissueTNM[meanBetasByTissueTCM %>% rownames(),]
heatmaply::heatmaply(
	file = "graphics/changeDNANormCancerbytRNA.html",
	(meanBetasByTissueTCM - meanBetasByTissueTCMx),
	#(meanBetasByTissueTCM - meanBetasByTissueTCMx)/meanBetasByTissueTCMx,
	main = "Differnce between Mean methylation in Normal and Cancer Samples by tRNA (Cancer - Normal)",
	limits=c(-1,1)
)
```

# Variance

```{r, fig.width = 6, fig.height = 7}
byVar <- function(x,name) {
	tRNAColc <- paste0("tRNA_",name)
	tRNACol <- sym(tRNAColc)
	varCol <- sym(paste0("var_",name))
	x %>%
		apply(1,var) %>% 
		as.data.frame() %>% 
		rownames_to_column(var = tRNAColc) %>% 
		rename(!!varCol := !!expr(.)) %>%
		arrange(desc(!!varCol)) %>%
		#mutate(!!tRNACol := as.factor(!!tRNACol)) %>%#as.ordered
		ggplot(aes(reorder(!!tRNACol,!!varCol),!!varCol)) + 
			geom_col() + 
			labs(
				x=name,
				y="variance"
			) +
			coord_flip()
}

byVar(meanBetasByTissueTNM,"normal") + 
byVar(meanBetasByTissueTCM,"cancer") +
plot_annotation(title = "tRNAs by rank order of variance")
```

# Session Info

```{r}
sessionInfo()
```

# References

